Reproducible radiomics through automated machine learning validated on twelve clinical applications

Radiomics uses quantitative medical imaging features to predict clinical outcomes. Currently, in a new clinical application, findingthe optimal radiomics method out of the wide range of available options has to be done manually through a heuristic trial-anderror process. In this study we propose a framework for automatically optimizing the construction of radiomics workflows perapplication. To this end, we formulate radiomics as a modular workflow and include a large collection of common algorithms foreach component. To optimize the workflow per application, we employ automated machine learning using a random search andensembling. We evaluate our method in twelve different clinical applications, resulting in the following area under the curves: 1)liposarcoma (0.83); 2) desmoid-type fibromatosis (0.82); 3) primary liver tumors (0.80); 4) gastrointestinal stromal tumors (0.77);5) colorectal liver metastases (0.61); 6) melanoma metastases (0.45); 7) hepatocellular carcinoma (0.75); 8) mesenteric fibrosis(0.80); 9) prostate cancer (0.72); 10) glioma (0.71); 11) Alzheimer’s disease (0.87); and 12) head and neck cancer (0.84). Weshow that our framework has a competitive performance compared human experts, outperforms a radiomics baseline, and performssimilar or superior to Bayesian optimization and more advanced ensemble approaches. Concluding, our method fully automaticallyoptimizes the construction of radiomics workflows, thereby streamlining the search for radiomics biomarkers in new applications.To facilitate reproducibility and future research, we publicly release six datasets, the software implementation of our framework,and the code to reproduce this study

Rule-making feedbacks through intermediation and evaluation in transnational private governance

Feedback from rule-making is an important facet of regulatory processes. By examining the operations of the Marine Stewardship Council (MSC), a transnational private certification program, we explore two types of feedback that operate within and outside R-I-T relationships and potentially influence agenda-setting and rule-reformulation. Within R-I-T relationships, intermediation feedback results from the knowledge that intermediaries acquire as they translate rules into practical forms applicable to specific regulatory targets. Intermediaries may communicate this knowledge to the regulator to strategically inform rule-reformulation. But the regulator may also have access to this information if transparency obligations come with the responsibility of performing intermediation functions. Outside R-I-T relationships, evaluation feedback involves external evaluative audiences—actors outside the regulatory process that hold an interest in evaluating and influencing that process. Transparency about R-I-T relationships should strengthen this feedback, though lack of information will not prevent external evaluators from rendering judgments and seeking to influence rule-reformulation

Structure, path dependence, and adaptation: North-South imbalances in transnational private fisheries governance

Transnational private governance schemes, like other global rule-making arenas, are confronted with the challenges of North-South imbalances. Through their standards and certification processes, private governance schemes aim to control access to the market for sustainably certified products and may consequently generate or perpetuate global inequalities. Are these imbalances inevitable and likely to persist? This article explores North-South imbalances in the operations of the Marine Stewardship Council (MSC), a leading standard-setting and certification scheme for capture fisheries. We examine whether the scheme's Northern-dominated origins reflect pre-existing structural imbalances, persist through path-dependent processes, or can be addressed by scheme adaptations. Our analysis uses data on the 312 fisheries that have engaged with the MSC from 1999 to 2015. We find evidence that imbalances in the MSC reflect corporate power and structures of power in the global fisheries sector, but that path dependence has also elevated the power of unexpected countries. Adaptations to date have been less successful as a means to lessen Northern dominance

Structure, path dependence, and adaptation: North-South imbalances in transnational private fisheries governance

Transnational private governance schemes, like other global rule-making arenas, are confronted with the challenges of North-South imbalances. Through their standards and certification processes, private governance schemes aim to control access to the market for sustainably certified products and may consequently generate or perpetuate global inequalities. Are these imbalances inevitable and likely to persist? This article explores North-South imbalances in the operations of the Marine Stewardship Council (MSC), a leading standard-setting and certification scheme for capture fisheries. We examine whether the scheme's Northern-dominated origins reflect pre-existing structural imbalances, persist through path-dependent processes, or can be addressed by scheme adaptations. Our analysis uses data on the 312 fisheries that have engaged with the MSC from 1999 to 2015. We find evidence that imbalances in the MSC reflect corporate power and structures of power in the global fisheries sector, but that path dependence has also elevated the power of unexpected countries. Adaptations to date have been less successful as a means to lessen Northern dominance

Transnational private governance between the logics of empowerment and control

Transnational private governance initiatives that address problems of social and environmental concern now pervade many sectors. In tackling distinct substantive problems, these programs have, however, prioritized different problem-oriented logics in their institutionalized rules and procedures. One is a "logic of control" that focuses on ameliorating environmental and social externalities by establishing strict and enforceable rules; another is a "logic of empowerment" that concentrates on remedying the exclusion of marginalized actors in the global economy. Examining certification programs in the areas of fair trade, organic agriculture, fisheries, and forest management, we assess the evolutionary effects of programs prioritizing one logic and then having to accommodate the other. The challenges programs face when balancing between the two logics, we argue, elucidate specific distributional consequences for wealth, power, and regulatory capabilities that private governance programs seek to overcome

Can technological innovations improve private regulation in the global economy?

Those supplying private regulation in the global economy face two fundamental challenges if they are to ameliorate the problems for which they create these systems: targets must conform to, while demanders must have proof of, regulatory compliance. This paper explores an important area absent from assessments as to whether, when, and how, private regulatory bodies are successful in improving behavior and rewarding compliant firms: the role of technological innovations. Employing an inductive, comparative case study analysis, we offer an analytical framework that distinguishes technological innovations that improve tracking mechanisms from innovations that directly improve on-the-ground performance. We illustrate the utility of the analytical framework through an assessment of technological innovations in shaping "non-state market driven" global certification programs governing forestry, fisheries, coffee, e-waste, and climate

Differential Diagnosis and Molecular Stratification of Gastrointestinal Stromal Tumors on CT Images Using a Radiomics Approach

Treatment planning of gastrointestinal stromal tumors (GISTs) includes distinguishing GISTs from other intra-abdominal tumors and GISTs' molecular analysis. The aim of this study was to evaluate radiomics for distinguishing GISTs from other intra-abdominal tumors, and in GISTs, predict the c-KIT, PDGFRA, BRAF mutational status, and mitotic index (MI). Patients diagnosed at the Erasmus MC between 2004 and 2017, with GIST or non-GIST intra-abdominal tumors and a contrast-enhanced venous-phase CT, were retrospectively included. Tumors were segmented, from which 564 image features were extracted. Prediction models were constructed using a combination of machine learning approaches. The evaluation was performed in a 100 × random-split cross-validation. Model performance was compared to that of three radiologists. One hundred twenty-five GISTs and 122 non-GISTs were included. The GIST vs. non-GIST radiomics model had a mean area under the curve (AUC) of 0.77. Three radiologists had an AUC of 0.69, 0.76, and 0.84, respectively. The radiomics model had an AUC of 0.52 for c-KIT, 0.56 for c-KIT exon 11, and 0.52 for the MI. The numbers of PDGFRA, BRAF, and other c-KIT mutations were too low for analysis. Our radiomics model was able to distinguish GISTs from non-GISTs with a performance similar to three radiologists, but less observer dependent. Therefore, it may aid in the early diagnosis of GIST, facilitating rapid referral to specialized treatment centers. As the model was not able to predict any genetic or molecular features, it cannot aid in treatment planning yet